University of Sistan and BaluchestanJournal of Natural Environmental Hazards2676-4377144420250622Forecasting the maximum temperature of the future periods in northwest Iran based on the CMIP6 climate modelsForecasting the maximum temperature of the future periods in northwest Iran based on the CMIP6 climate models118853110.22111/jneh.2024.47321.2006FARoghayehMaleki MereshtPostdoctoral Researcher, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.BroumandSalahiProfessor of Climatology, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, IranMahnazSaberPostdoctoral Researcher, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, IranJournal Article20231129One of the most important challenges for mankind is the issue of climate change and how to face the dangers caused by it. The purpose of this research was to forecast the maximum temperature in northwest Iran based on CMIP6 climate models. For this purpose, after trending the maximum temperature data of 12 selected stations in the northwest of Iran from 1985 to 2014 using the Man-Kendall test, maximum temperatures were simulated in SDSM6.1 using (SSP 2-4.5) and (SSP 5-8.5) scenarios of CanEsm5, MPI-ESMI-2HR models and predicted for the next 30 years. To evaluate the performance of CMIP6 models and compare the basic and predicted values, 3 statistical measures are used. Including Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results of trending by the Man-Kendall method indicated a significant upward trend at the 99% confidence level in all stations except Jolfa station. The results of maximum temperature modeling showed that the CanESM5 model has less error and more accuracy in predicting the maximum temperature compared to the MPI-ESMI-2HR model. According to the results, an increase in temperature will be experienced in all stations and all months of the year in the coming decades, and the amount of this increase was higher in (SSP 5.8.5) scenario. In general, according to the findings, the highest percentage of temperature increase in all stations will occur in the cold months and often in late autumn and winter. Based on the results, the maximum temperature in all stations will increase from 0.2℃ to 2℃. Tekab, Urmia, and Maragheh stations with a 12-13% increase, and Mako and Jolfa with a 6% increase will experience the highest and lowest increase in maximum temperature, respectively, compared to other stations.One of the most important challenges for mankind is the issue of climate change and how to face the dangers caused by it. The purpose of this research was to forecast the maximum temperature in northwest Iran based on CMIP6 climate models. For this purpose, after trending the maximum temperature data of 12 selected stations in the northwest of Iran from 1985 to 2014 using the Man-Kendall test, maximum temperatures were simulated in SDSM6.1 using (SSP 2-4.5) and (SSP 5-8.5) scenarios of CanEsm5, MPI-ESMI-2HR models and predicted for the next 30 years. To evaluate the performance of CMIP6 models and compare the basic and predicted values, 3 statistical measures are used. Including Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results of trending by the Man-Kendall method indicated a significant upward trend at the 99% confidence level in all stations except Jolfa station. The results of maximum temperature modeling showed that the CanESM5 model has less error and more accuracy in predicting the maximum temperature compared to the MPI-ESMI-2HR model. According to the results, an increase in temperature will be experienced in all stations and all months of the year in the coming decades, and the amount of this increase was higher in (SSP 5.8.5) scenario. In general, according to the findings, the highest percentage of temperature increase in all stations will occur in the cold months and often in late autumn and winter. Based on the results, the maximum temperature in all stations will increase from 0.2℃ to 2℃. Tekab, Urmia, and Maragheh stations with a 12-13% increase, and Mako and Jolfa with a 6% increase will experience the highest and lowest increase in maximum temperature, respectively, compared to other stations.https://jneh.usb.ac.ir/article_8531_0863a0cd28fa5981a48b0de9dbbd455a.pdfUniversity of Sistan and BaluchestanJournal of Natural Environmental Hazards2676-4377144420250622Monitoring and zoning of long-term variation of the DSI in the eastern half of IranMonitoring and zoning of long-term variation of the DSI in the eastern half of Iran1936878610.22111/jneh.2025.48604.2040FAMehdiRahnamaAssociate Professor, Sand and Dust Storm International Research Center (SDS-IRC), Research Institute of Meteorology and Atmospheric Science (RIMAS), Tehran, IranFaezehNooriPhD student of Meteorology, Researcher, Sand and Dust Storm International Research Center (SDS-IRC), Research Institute of Meteorology and Atmospheric Science (RIMAS), Tehran, IranSavizSehat KashaniAssociate Professor, Sand and Dust Storm International Research Center (SDS-IRC), Research Institute of Meteorology and Atmospheric Science (RIMAS), Tehran, IranNoushinKhoddamPhD in Meteorology, Researcher, Sand and Dust Storm International Research Center (SDS-IRC), Research Institute of Meteorology and Atmospheric Science (RIMAS), Tehran, IranJournal Article20240429Climate change is an important factor that increases the risks of wind erosion and dust storms. To study the frequency and intensity of the dust phenomenon in the eastern half of the country, the Dust Storm Index was used between 2002 and 2023. Based on the DSI, profiles of the frequency and intensity of dust storms in the study area were calculated using the geostatistical interpolation methods of Inverse distance weighted interpolation. In general, the time series of the dust storm index during the 2002–2023 statistical period showed a significant increasing trend in the Razavi Khorasan, South Khorasan, and North Khorasan. In Sistan and Baluchestan, we observed more irregular variation and no significant trends. The Zabol and Sarkhs stations had the highest number of dust storms. The results showed that the monthly average variation in the DSI in the first eight months of the year generally increased. The DSI decreased in the months following December. In terms of geographical distribution, the DSI showed higher values in the eastern and southeastern halves, and the lowest values in the northeastern regions. Analyzing the trend of variations of this index in the half-east, north-east, and south-east of the country, in addition to the south-east parts of the country, in recent years the eastern parts of Razavi Khorasan have also been involved in this phenomenon. The formation of low pressure in the southwest of Afghanistan, northwest Pakistan, and east of Iran, simultaneously with the establishment of high pressure in the north of Afghanistan and northeast of Iran, causes the creation of an intensive pressure gradient and relatively strong surface winds. These conditions activated internal and transboundary sources of dust in the study area, leading to the spread and transfer of dust to the eastern half of Iran.Climate change is an important factor that increases the risks of wind erosion and dust storms. To study the frequency and intensity of the dust phenomenon in the eastern half of the country, the Dust Storm Index was used between 2002 and 2023. Based on the DSI, profiles of the frequency and intensity of dust storms in the study area were calculated using the geostatistical interpolation methods of Inverse distance weighted interpolation. In general, the time series of the dust storm index during the 2002–2023 statistical period showed a significant increasing trend in the Razavi Khorasan, South Khorasan, and North Khorasan. In Sistan and Baluchestan, we observed more irregular variation and no significant trends. The Zabol and Sarkhs stations had the highest number of dust storms. The results showed that the monthly average variation in the DSI in the first eight months of the year generally increased. The DSI decreased in the months following December. In terms of geographical distribution, the DSI showed higher values in the eastern and southeastern halves, and the lowest values in the northeastern regions. Analyzing the trend of variations of this index in the half-east, north-east, and south-east of the country, in addition to the south-east parts of the country, in recent years the eastern parts of Razavi Khorasan have also been involved in this phenomenon. The formation of low pressure in the southwest of Afghanistan, northwest Pakistan, and east of Iran, simultaneously with the establishment of high pressure in the north of Afghanistan and northeast of Iran, causes the creation of an intensive pressure gradient and relatively strong surface winds. These conditions activated internal and transboundary sources of dust in the study area, leading to the spread and transfer of dust to the eastern half of Iran.https://jneh.usb.ac.ir/article_8786_715caa8e3cb68c4f37aa8e81730c8fdc.pdfUniversity of Sistan and BaluchestanJournal of Natural Environmental Hazards2676-4377144420250622Comparison and prioritization of environmental threats in natural habitats of mangrove forests of IranComparison and prioritization of environmental threats in natural habitats of mangrove forests of Iran3762873810.22111/jneh.2024.48629.2041FARoghayehGarmaeepourPhD student, Department of Environment, Faculty of Natural Resources, University of Tehran, Karaj, IranAfshinDanehkarProfessor, Department of Environment, Faculty of Natural Resources, University of Tehran, Karaj, IranAmirAlambeigiAssistant professor, Department of Agricultural Extension and Education, Faculty of Agriculture, University of Tehran, Karaj, IranAfshinAlizadeh ShabaniAssociate professor, Department of Environment, Faculty of Natural Resources, University of Tehran, Karaj, IranParvanehSobhaniPostdoctoral Researcher, Department of Environment, Faculty of Natural Resources, University of Tehran, Karaj, IranJournal Article20240503Today, mangroves around the world have faced many risks under the influence of local economic pressures, biophysical stimuli, and socio-ecological systems, and the identification and prioritization of these pressures and threatening factors is of great importance. Therefore, in the present study, to identify threatening drivers in different habitats of this region, we evaluated the threatening factors in the framework of the DPSIR conceptual model, including the driving force (D), pressure (P), situation (S), effect (I), and response (R). Threatening drivers in different habitats were also compared and prioritized. As the results showed, 16 threatening drivers of human and environmental origin were identified in these habitats, in this regard, 90 threatening factors have led to the occurrence of environmental hazards in the region. Among these factors, 37 with a score above 70% were observed among the different habitats. In addition, the most threatening drivers and pressures affecting Iran's mangrove forests were related to the habitat of Qeshm-Khorkhoran Island, and the least pressures and threats were related to the habitat of the city. In addition, among the threats identified in the region, inappropriate rainfall regimes (lack of rainfall) can be seen as the most important environmental threat factor among different habitats. The obtained results indicate that some habitats such as Qeshm-Khorkhoran, Mardo Island, Pol, and Kolghan, which are affected by several threatening factors and environmental pressures, should be prioritized for management and planning activities. Controlling these threats requires integrated planning and management at the regional level.Today, mangroves around the world have faced many risks under the influence of local economic pressures, biophysical stimuli, and socio-ecological systems, and the identification and prioritization of these pressures and threatening factors is of great importance. Therefore, in the present study, to identify threatening drivers in different habitats of this region, we evaluated the threatening factors in the framework of the DPSIR conceptual model, including the driving force (D), pressure (P), situation (S), effect (I), and response (R). Threatening drivers in different habitats were also compared and prioritized. As the results showed, 16 threatening drivers of human and environmental origin were identified in these habitats, in this regard, 90 threatening factors have led to the occurrence of environmental hazards in the region. Among these factors, 37 with a score above 70% were observed among the different habitats. In addition, the most threatening drivers and pressures affecting Iran's mangrove forests were related to the habitat of Qeshm-Khorkhoran Island, and the least pressures and threats were related to the habitat of the city. In addition, among the threats identified in the region, inappropriate rainfall regimes (lack of rainfall) can be seen as the most important environmental threat factor among different habitats. The obtained results indicate that some habitats such as Qeshm-Khorkhoran, Mardo Island, Pol, and Kolghan, which are affected by several threatening factors and environmental pressures, should be prioritized for management and planning activities. Controlling these threats requires integrated planning and management at the regional level.https://jneh.usb.ac.ir/article_8738_52f6667b3c5cfe166dd9e9c8f92fd9dc.pdfUniversity of Sistan and BaluchestanJournal of Natural Environmental Hazards2676-4377144420250622Analysis of Precipitation Extremes Trends in the Persian Gulf and Oman Sea Basin in Southern IranAnalysis of Precipitation Extremes Trends in the Persian Gulf and Oman Sea Basin in Southern Iran6388876310.22111/jneh.2025.48651.2043FAPeymanMahmoudiAssociate Professor, Department of Physical Geography, University of Sistan and Baluchestan, Zahedan, IranEbrahimFattahiAssociate Professor, Atmospheric Science and Meteorological Research Center, Tehran, IranMohsenHeydariMSc. of Agricultural Engineering, Sistan and Baluchestan Province Meteorological Administration, Zahedan, IranAllahbakhshRigiMSc. of Mathematics, Sistan and Baluchestan Province Meteorological Administration, Zahedan, IranAtefehAnsariMSc. of Climatology, Department of Physical Geography, University of Sistan and Baluchestan, Zahedan, IranAlirezaGhaemiPostdoc Researcher, Department of Physical Geography, University of Sistan and Baluchestan, Zahedan, IranJabbarRezaeiPhD student of Climatology, Geography Department, University of Zanjan, Zanjan, IranJournal Article20240505In this research, to analyze the trends of precipitation extremes in the Persian Gulf and Oman Sea Basin, daily precipitation data from 47 meteorological stations over 30 years (1993-2022) were used. Fifteen precipitation extreme indices were extracted for all the studied stations, and their long-term trends were analyzed using Sen's slope estimator. The results indicated a decreasing trend in the annual total precipitation on wet days for the western and central parts and an increasing trend for the eastern parts of the Persian Gulf and Oman Sea Basin. Consistent with the decreasing trend in annual total precipitation, these two parts of the studied basin experienced a decrease in the number of days with heavy rains (more than 10 mm), very heavy rains (more than 20 mm), extremely heavy rains (more than 30 mm), and maximum consecutive 1-day, 3-day, and 5-day precipitations. However, in the eastern part of the studied basin, the trend of maximum length of dry spells was decreasing. In line with this trend, the number of days with heavy rains (more than 10 mm), very heavy rains (more than 20 mm), extremely heavy rains (more than 30 mm), and maximum consecutive 1-day, 3-day, and 5-day precipitations also showed increasing trends.In this research, to analyze the trends of precipitation extremes in the Persian Gulf and Oman Sea Basin, daily precipitation data from 47 meteorological stations over 30 years (1993-2022) were used. Fifteen precipitation extreme indices were extracted for all the studied stations, and their long-term trends were analyzed using Sen's slope estimator. The results indicated a decreasing trend in the annual total precipitation on wet days for the western and central parts and an increasing trend for the eastern parts of the Persian Gulf and Oman Sea Basin. Consistent with the decreasing trend in annual total precipitation, these two parts of the studied basin experienced a decrease in the number of days with heavy rains (more than 10 mm), very heavy rains (more than 20 mm), extremely heavy rains (more than 30 mm), and maximum consecutive 1-day, 3-day, and 5-day precipitations. However, in the eastern part of the studied basin, the trend of maximum length of dry spells was decreasing. In line with this trend, the number of days with heavy rains (more than 10 mm), very heavy rains (more than 20 mm), extremely heavy rains (more than 30 mm), and maximum consecutive 1-day, 3-day, and 5-day precipitations also showed increasing trends.https://jneh.usb.ac.ir/article_8763_326f262bad8b1df0b09b1b18968f51f3.pdfUniversity of Sistan and BaluchestanJournal of Natural Environmental Hazards2676-4377144420250622The Impact of Natural Disasters on Economic Growth in Selected Asian CountriesThe Impact of Natural Disasters on Economic Growth in Selected Asian Countries89104890010.22111/jneh.2025.48712.2046FAFatemehArdaliPh.D. student of Agricultural Economics, School of Agriculture, Shiraz University, Shiraz, Iran0009-0003-0394-3573Mohammad HassanTarazkarAssociate Professor of Agricultural Economics, School of Agriculture, Shiraz University, Shiraz, IranJournal Article20240511In recent years, a significant increase in the frequency and intensity of natural disasters has led to the loss of capital and human lives. Evidence suggests that each country’s economic growth is affected by natural disasters. Additionally, economic growth in developing countries is more sensitive to natural disasters than in developed countries. Therefore, this study examined the impact of natural disasters on economic growth during 2001-2020 using the Panel Autoregressive Distributed Lag (Panel-ARDL) model in six Asian countries that had the highest mortality rates from natural disasters. Also, Iran, Indonesia, Bangladesh, Pakistan, the Philippines, and India were studied in this paper. Additionally, the impact of other variables, such as the working population, foreign investment, human development index, government size, and economic complexity index, on economic growth has been examined. The empirical results show that natural disasters have a significant negative effect on economic growth in the short and long terms. Moreover, the size of the government harms economic growth. On the other hand, the working population, foreign investment, human development index, and economic complexity had a significant positive effect on economic growth.In recent years, a significant increase in the frequency and intensity of natural disasters has led to the loss of capital and human lives. Evidence suggests that each country’s economic growth is affected by natural disasters. Additionally, economic growth in developing countries is more sensitive to natural disasters than in developed countries. Therefore, this study examined the impact of natural disasters on economic growth during 2001-2020 using the Panel Autoregressive Distributed Lag (Panel-ARDL) model in six Asian countries that had the highest mortality rates from natural disasters. Also, Iran, Indonesia, Bangladesh, Pakistan, the Philippines, and India were studied in this paper. Additionally, the impact of other variables, such as the working population, foreign investment, human development index, government size, and economic complexity index, on economic growth has been examined. The empirical results show that natural disasters have a significant negative effect on economic growth in the short and long terms. Moreover, the size of the government harms economic growth. On the other hand, the working population, foreign investment, human development index, and economic complexity had a significant positive effect on economic growth.https://jneh.usb.ac.ir/article_8900_31eba2a9bc8aa849c596ad706e98c09c.pdfUniversity of Sistan and BaluchestanJournal of Natural Environmental Hazards2676-4377144420250622Analyzing the Threats of Climate Change and Land Use Changes on Increasing Flood Risk in the Shahrchay Drainage BasinAnalyzing the Threats of Climate Change and Land Use Changes on Increasing Flood Risk in the Shahrchay Drainage Basin105126854710.22111/jneh.2024.49039.2053FATayebehIraniPhD graduate, Department of Range and Watershed Management, Faculty of Natural Resources, Urmia University, Urmia, IranHiradAbghariAssociate Professor, Department of Range and Watershed Management, Faculty of Natural Resources, Urmia University, Urmia, Iran0000-0002-3407-3297Ali AkbarRasouliProfessor Department Faculty of Science and Engineering, Macquarie University, Sydney, NSW, AustraliaJournal Article20240613This study investigated the factors influencing flood proneness and predicted future flood risks in the Shahrchay watershed, located in West Azerbaijan Province, a sub-basin of the Urmia Lake watershed. Given population growth, social and economic development, and climatic changes due to global warming, flood damage in this region is increasing. This study aimed to identify the main factors affecting flood risk and predict the likelihood of future floods. To achieve the stated goal, first, for monitoring and evaluating land use changes in the last seven years, Sentinel2 images were used using an object-oriented method and image classification from the SVM algorithm, and for simulating future land use changes, the CA-MARKOV algorithm was used. Finally, runoff simulation using the InVEST model was introduced to the InVEST software from the variables of precipitation (for precipitation simulation, LARS-WG software, the CMIP6 climate model named ACCESS-CM2, and two scenarios SSP2-4.5 and SSP5-8.5), land use, hydrological soil group, and curve number related to the study watershed. The final results show that for 2016, 2023, and 2030, the southern side of the Shahrchay watershed has a very low flood potential. In the central part of the watershed, the potential for runoff production was medium and high. According to the prediction results for 2030, the maximum and minimum runoff production potentials were estimated with numerical values of 129.57 and 0 cubic meters, respectively. Therefore, runoff will increase in most parts of the Shahrchay watershed.This study investigated the factors influencing flood proneness and predicted future flood risks in the Shahrchay watershed, located in West Azerbaijan Province, a sub-basin of the Urmia Lake watershed. Given population growth, social and economic development, and climatic changes due to global warming, flood damage in this region is increasing. This study aimed to identify the main factors affecting flood risk and predict the likelihood of future floods. To achieve the stated goal, first, for monitoring and evaluating land use changes in the last seven years, Sentinel2 images were used using an object-oriented method and image classification from the SVM algorithm, and for simulating future land use changes, the CA-MARKOV algorithm was used. Finally, runoff simulation using the InVEST model was introduced to the InVEST software from the variables of precipitation (for precipitation simulation, LARS-WG software, the CMIP6 climate model named ACCESS-CM2, and two scenarios SSP2-4.5 and SSP5-8.5), land use, hydrological soil group, and curve number related to the study watershed. The final results show that for 2016, 2023, and 2030, the southern side of the Shahrchay watershed has a very low flood potential. In the central part of the watershed, the potential for runoff production was medium and high. According to the prediction results for 2030, the maximum and minimum runoff production potentials were estimated with numerical values of 129.57 and 0 cubic meters, respectively. Therefore, runoff will increase in most parts of the Shahrchay watershed.https://jneh.usb.ac.ir/article_8547_750cf1548a147323a6406eb9f2f0ec04.pdfUniversity of Sistan and BaluchestanJournal of Natural Environmental Hazards2676-4377144420250622Utilization of Environmental Risk Indices for Site Selection in the Construction of River Floodwalls in Southern Kerman ProvinceUtilization of Environmental Risk Indices for Site Selection in the Construction of River Floodwalls in Southern Kerman Province127146876210.22111/jneh.2025.49125.2055FASaeedeh ‎ShahrekiFormer M.Sc. Student, Department of Environment, Faculty of Natural Resources, University of Zabol, Zabol, IranMaliheErfaniAssociate Professor , Department of Environment, Faculty of Natural Resources, University of Zabol, Zabol, IranFatemehJahanishakibAssistant Professor of Environmental Sciences, Faculty of Natural Resources and Environment, University of Birjand, Birjand, IranFatemehEinollahi PeerAssistant Professor, Department of Environment, Faculty of Natural Resources, University of Zabol, Zabol, IranJournal Article20240622The increasing frequency and severity of flood hazards in recent years have necessitated greater attention to the strategic implementation of both biological and physical flood control measures. This study focuses on physical interventions, specifically river floodwalls, as a short-term solution to mitigate flood damage. The study area encompasses the southern region of Kerman Province, including the seven counties of Faryab, Kohnoorj, Jiroft, Manujan, Anbarabad, Qaleh Ganj, and Rudbar Jonoob, which are predominantly high-risk zones for river overflow-induced flooding. To determine optimal sites for river floodwall construction, environmental risk indices were employed, comprising two key layers: flood hazard and flood susceptibility. The flood hazard assessment incorporated ecological criteria, including water availability (precipitation and runoff accumulation), permeability (surface roughness, soil type, and NDVI), and landform characteristics (slope). Meanwhile, socio-economic flood susceptibility was evaluated based on proximity to transportation networks, residential areas, tourist sites, and agricultural land. The criteria for flood hazard indices were standardized, and a hierarchical weighting method was applied. The hazard indices were calculated by combining the ecological criteria using the linear weighted combination (WLC) method. The resultant flood hazard index was then intersected with each socio-economic susceptibility criterion to identify high-risk and vulnerable areas for each category. The findings reveal that 56% of agricultural land and 48% of built-up areas fall within flood risk zones. Moreover, 24% of the transportation network lies in these zones, while none of the assessed tourist sites are situated within high-risk areas. Additionally, 182 kilometers of the province’s rivers-accounting for 2% of the total river length—were identified as requiring floodwall construction to mitigate risks in sensitive socio-economic zones. The outcomes of this study provide valuable insights for decision-makers aiming to reduce environmental and socio-economic damages caused by floods. Furthermore, the methodology employed offers a replicable framework for similar studies in other regions.The increasing frequency and severity of flood hazards in recent years have necessitated greater attention to the strategic implementation of both biological and physical flood control measures. This study focuses on physical interventions, specifically river floodwalls, as a short-term solution to mitigate flood damage. The study area encompasses the southern region of Kerman Province, including the seven counties of Faryab, Kohnoorj, Jiroft, Manujan, Anbarabad, Qaleh Ganj, and Rudbar Jonoob, which are predominantly high-risk zones for river overflow-induced flooding. To determine optimal sites for river floodwall construction, environmental risk indices were employed, comprising two key layers: flood hazard and flood susceptibility. The flood hazard assessment incorporated ecological criteria, including water availability (precipitation and runoff accumulation), permeability (surface roughness, soil type, and NDVI), and landform characteristics (slope). Meanwhile, socio-economic flood susceptibility was evaluated based on proximity to transportation networks, residential areas, tourist sites, and agricultural land. The criteria for flood hazard indices were standardized, and a hierarchical weighting method was applied. The hazard indices were calculated by combining the ecological criteria using the linear weighted combination (WLC) method. The resultant flood hazard index was then intersected with each socio-economic susceptibility criterion to identify high-risk and vulnerable areas for each category. The findings reveal that 56% of agricultural land and 48% of built-up areas fall within flood risk zones. Moreover, 24% of the transportation network lies in these zones, while none of the assessed tourist sites are situated within high-risk areas. Additionally, 182 kilometers of the province’s rivers-accounting for 2% of the total river length—were identified as requiring floodwall construction to mitigate risks in sensitive socio-economic zones. The outcomes of this study provide valuable insights for decision-makers aiming to reduce environmental and socio-economic damages caused by floods. Furthermore, the methodology employed offers a replicable framework for similar studies in other regions.https://jneh.usb.ac.ir/article_8762_9f9d9208b2f248d38c814f28d5624032.pdfUniversity of Sistan and BaluchestanJournal of Natural Environmental Hazards2676-4377144420250622The effect of psychological distance on climate concerns and drought adaptation behaviors of farmers in Shushtar CountyThe effect of psychological distance on climate concerns and drought adaptation behaviors of farmers in Shushtar County147164878710.22111/jneh.2025.49129.2056FAMoslemSavariAssociate Prof. Department of Agricultural Extension and Education, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, IranMohammad RezaShahpasandAssociate Prof. Higher Education Institute of Applied Science, Ministry of Jihad-Keshavarzi, Tehran, IranJournal Article20240622The primary aim of this research is to examine the impact of psychological distance on farmers' adaptation behaviors to drought, with climate concerns serving as a mediating factor. The study's statistical population comprises all farmers in Shushtar City, Khuzestan Province. A sample size of 395 individuals was determined using the Krejcie and Morgan table, and a multi-stage sampling method with proportional assignment was employed. The data collection instrument was a questionnaire, whose form and content validity were confirmed by faculty members from the Agricultural Sciences and Natural Resources University of Khuzestan. The reliability of the questionnaire was established through Cronbach's alpha. The Average Variance Extracted (AVE) index was utilized to assess convergent validity, while the Composite Reliability (CR) index was employed to determine the model's reliability. This research indicated that the dimensions of psychological distance (geographical, social, temporal, and hypothetical) account for 72.2% of the variance in climate concerns. Additionally, the research variables were able to explain 65.5% of the variance in the use of adaptive behaviors. The results of this research are crucial for agricultural activists and officials to understand how farmers perceive the risks of climate change and drought, and how they are influenced by adopting adaptation methods. This knowledge is essential for developing effective drought strategies.The primary aim of this research is to examine the impact of psychological distance on farmers' adaptation behaviors to drought, with climate concerns serving as a mediating factor. The study's statistical population comprises all farmers in Shushtar City, Khuzestan Province. A sample size of 395 individuals was determined using the Krejcie and Morgan table, and a multi-stage sampling method with proportional assignment was employed. The data collection instrument was a questionnaire, whose form and content validity were confirmed by faculty members from the Agricultural Sciences and Natural Resources University of Khuzestan. The reliability of the questionnaire was established through Cronbach's alpha. The Average Variance Extracted (AVE) index was utilized to assess convergent validity, while the Composite Reliability (CR) index was employed to determine the model's reliability. This research indicated that the dimensions of psychological distance (geographical, social, temporal, and hypothetical) account for 72.2% of the variance in climate concerns. Additionally, the research variables were able to explain 65.5% of the variance in the use of adaptive behaviors. The results of this research are crucial for agricultural activists and officials to understand how farmers perceive the risks of climate change and drought, and how they are influenced by adopting adaptation methods. This knowledge is essential for developing effective drought strategies.https://jneh.usb.ac.ir/article_8787_1eb874cf56ab85153029b30aa7f77ffb.pdf